Strategic emerging industries (SEIs) represent the future direction of industrial developments and are crucial in stimulating the overall and long-term development for economy and society. The government plays a key role in promoting the development of SEIs. This paper, for the first time, investigates the cooperation relationship among innovation members, such as enterprises, universities and research institutes in a collaborative innovation network of strategic emerging industries under government intervention. A three-population evolutionary game theory approach was employed under different scenarios for the government acting as the stakeholder, considering the non-profit, definite fit as well as uncertain profit when incentive and punishment policies are adopted. A novel evolutionary game model of the cooperation relationship among collaborative innovation network members under government’s intervention is established. The results of the simulation experiments show that government’s intervention significantly influences the cooperation relationship between enterprises, universities and research institutes. When the sum of financial incentives and punishments is greater than the total additional cost (TAC), enterprises, universities and research institutes should pay for collaborative innovation. Moreover, government’s financial intervention can effectively promote the cooperation between enterprises, universities and research institutes.
In dealing with complex and ill-defined systems of an offshore application, modelling of human reasoning for the purpose of risk assessment requires the effectiveness of a systematic logic-based approach. Floating production, storage and offloading (FPSO) installations, for example, combine traditional process technology with marine technology, and thus are quite dependent on technical design and operational safety control. Such safety-critical dependencies require novel approaches to properly analyse the risk involved. Hence, a proposed framework utilising approximate reasoning and evidential reasoning approaches is provided for modelling the assessment task. As based on fuzzy set theory, the model enables uncertainties to be described mathematically and further processed in the analysis of the structures. The forms of membership functions that could be used in representing fuzzy linguistic variables to quantify risk levels are presented. A case study of collision risk between FPSO and shuttle tanker due to technical failure during tandem offloading operation is used in this paper to illustrate the application of the proposed model. Furthermore, the obtained results from the case study provide confirmation that at various stages of offshore engineering systems design process the framework of incorporated approximate reasoning is a suited and convenient tool for attaining reliable risk analysis.
The innovation of the biomedical engineering (BME) industry is inseparable from its cooperation with medical institutions. China has considerable medical institutions. Although private hospitals account for more than half of Chinese medical institutions, they rarely participate in biomedical engineering industry innovation. This paper analyzed the collaborative relationship among biomedical engineering enterprises, universities, research institutes, public hospitals and private hospitals through evolutionary game theory and discussed the influence of different factors on the collaborative innovation among them. A tripartite evolutionary game model is established which regards private hospitals as a stakeholder. The results show that (1) the good credit of private hospitals has a positive effect on their participation in collaborative innovation; (2) it is helpful for BME collaborative innovation to enhance the collaborative innovation ability of partners; (3) the novelty of innovation projects has an impact on BME collaborative innovation. The specific impacts depend on the revenue, cost and risk allocation ratio of innovation partners; (4) the higher the practicability of innovation projects, the more conducive to collaborative innovation.
Due to the following characteristics of offshore program, such as one-time large-scale investment, comprehensive high-risk, long payback period, high uncertainty, high regional and political, the investors has been paid more and more attentions to the risk of offshore program. Combined with the characteristics of offshore program risk management, and with the use of BP neural network theory, this paper constructed "the Offshore Program Risk Comprehensive Assessment index system" and "Assessment Model". Combined with BP network learning process, and on the basis of selecting risk-related parameters and setting different network training layers, this paper simulated the BP model and analyzed the results.
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